I-Corps: Bio-Inspired Predictive Engineering Analysis Tool

I-Corps：仿生预测工程分析工具

• 批准号: 1737815
• 负责人: Devinder Kaur
• 金额: $ 5万
• 依托单位: University of Toledo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1737815&HistoricalAwards=false
• 关键词: Corps; Bio; Inspired; Predictive; Engineering

The broader impact/commercial potential of this I-Corps project is to obtain the benefits available from modernizing legacy processes in the made-to-order design manufacturing industry. Traditionally the mathematical processes used to analyze potential designs are very linear in nature, and do not offer the manufacturer a complete picture of the overall impacts of the non-linear parts of their designs. With the predictive engineering analysis tool developed here, a manufacturing facility can preview the results available from using a particular engineering design prior to the actual manufacturing and testing of the physical parts. Design parameters and environmental conditions can also be inserted into the tool which are then used to better predict the behavior of the part after it is produced. This innovative virtual tool has the potential to be added to the set of existing design and testing tools already being used and let manufacturers predict the success or failure of a part. The impact of this tool would be decreased time to market, eliminating the guesswork now used in certain aspects of a design and saving valuable physical resources.This I-Corps project defines an innovative scalable software tool that is capable of virtually predicting the success or failure of an engineering design prior to production. The technique is based on the mathematical modeling of the coordinated behaviors of biological system. This allows the tool to quickly search and intelligently predict the best solution sets to a multi-objective problem in a given design space. This project employs these innovative bio-inspired techniques to develop algorithms which are applied to engineering designs to produce an ideal set of solutions based on user defined objectives. Bio-inspired algorithms have been shown to improve upon current standard rigid mathematical techniques. This project provides the flexibility to implement an approach that is able to search the entire problem space at once therefore giving better visibility to all of the possible solutions. Since no particular parameter in isolation impacts the outcome of the algorithm, the user is presented with the opportunity to shift the input parameters and rerun the optimization. Further this I-Corps project attempts to explore and define the input parameters for a variety of industries, and assist the end user in coming up with better designs for their products.

该I-Corps项目的更广泛的影响/商业潜力是从现代化的订单设计制造业中获得现代化的遗产流程可获得的好处。传统上，用于分析潜在设计的数学过程本质上是非常线性的，并且没有为制造商提供设计非线性部分的整体影响。通过此处开发的预测工程分析工具，制造工厂可以在实际制造和测试物理部件之前使用特定的工程设计可获得的结果。设计参数和环境条件也可以插入工具中，然后将其用于更好地预测零件产生后的行为。这种创新的虚拟工具有可能将其添加到已经使用的现有设计和测试工具集中，并让制造商预测零件的成功或失败。该工具的影响将减少上市时间，消除了现在在设计的某些方面使用的猜测，并节省了宝贵的物理资源。本I-Corps项目定义了一种创新的可扩展软件工具，该工具能够实际上预测生产前工程设计的成功或失败。该技术基于生物系统协调行为的数学建模。这使工具可以快速搜索并智能预测给定设计空间中多目标问题的最佳解决方案集。该项目采用这些创新的生物启发的技术来开发算法，这些算法应用于工程设计，以基于用户定义的目标生产一套理想的解决方案。已经证明，以生物启发的算法可以改善当前标准刚性数学技术。该项目提供了实现能够一次搜索整个问题空间的方法的灵活性，从而可以更好地了解所有可能的解决方案。由于没有孤立的特定参数会影响算法的结果，因此向用户提供了移动输入参数并重新运行优化的机会。 此外，该I-Corps项目试图探索和定义各种行业的输入参数，并协助最终用户为其产品提供更好的设计。